COVID-19 Prediction Model: A Literature Survey

[1] Yifan Yang, Wenwu Yu, Duxin Chen, “Prediction of COVID-19 spread via LSTM and the deterministic SEIR model”, 2020, 39th Chinese Control Conference(CCC)
[2] Zainab Abbas AbdulhusseinAlwaeli, Abdullahi Abdu Ibrahim, “Predicting Covid-19 Trajectory Using Machine Learning”, 2020, 4th International Symposium on Multidisciplinary Studies and Innovative Technologies(ISMSIT)
[3] Suraj Bodapati, Harika Bandarupally, M Trupthi, “COVID-19 Time Series Forecasting of Daily Cases, Deaths Caused and Recovered Cases using Long Short Term Memory Networks”, 2020, IEEE 5th International Conference on Computing
Communication and Automation(ICCCA)
[4] Hanqing Chao, Xi Fang, Pingkun Yan, “Integrative analysis for COVID-19 patient outcome prediction”, 2020, Medical ImageAnalysis
[5] Danish Rafiq, Suhail Ahmad Suhail, Mohammad Abid Bazaz, “Evaluation and prediction of COVID-19 in India: A case study of worst hit states”, 2020, Chaos, Solitons &Fractals
[6] Farah Shahid, AneelaZameer, Muhammad Muneeb, “Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM”, 2020, Chaos, Solitons &Fractals
[7] Anwar Jarndal, Saddam Husain, Omar Zaatar, Talal Al Gumaei, Amar Hamadeh, “GPR and ANN based Prediction Models for COVID-19 Death Cases”, 2020, International Conference on Communications, Computing, Cybersecurity, and
Informatics(CCCI)
[8] Pratima Kumari, Durga Toshniwal, “Real-time estimation of COVID-19 cases using machine learning and mathematical models – The case of India”, 2020, IEEE 15th International Conference on Industrial and Information Systems(ICIIS)
[9] Yasin Khan, Pritam Khan, Sudhir Kumar, Jawar Singh, Rajesh M. Hegde, “Detection and Spread Prediction of COVID-19 from Chest X-ray Images using Convolutional Neural Network-Gaussian Mixture Model”, 2020, IEEE 17th India Council
International Conference (INDICON)
[10] Choujun Zhan, Yufan Zheng, Haijun Zhang, Quansi Wen, “Random-Forest-Bagging Broad Learning System with Applications for COVID-19 Pandemic”, 2021, IEEE Internet of Things Journal
[11] Yifan Yang, Wenwu Yu, Duxin Chen, “Prediction of COVID-19 spread via LSTM and the deterministic SEIR model”, 2020, 39th Chinese Control Conference (CCC)
[12] Leonardo Sestrem de Oliveira, Sarah Beatriz Gruetzmacher, João Paulo Teixeira, “COVID-19 Time Series Prediction”, 2021, Procedia ComputerScience
[13] Durga Prasad Kavadi, Rizwan Patan, Amir H. Gandomi, “Partial derivative Nonlinear Global Pandemic Machine Learning prediction of COVID 19”, 2020, Chaos, Solitons & Fractals
[14] Ankan Ghosh Dastider, Farhan Sadik, Shaikh Anowarul Fattah, “An integrated autoencoder-based hybrid CNN-LSTM model for COVID-19 severity prediction from lung ultrasound”, 2021, Computers in Biology and Medicine
[15] Abhishek Dixit, Ashish Mani, Rohit Bansal, “CoV2-Detect-Net: Design of COVID-19 predictionmodelbasedonhybridDE-PSOwithSVMusingChestX-rayimages”,2021, Information Sciences
[16] Elena Casiraghi, Dario Malchiodi, Gabriella Trucco, Marco Frasca, Luca Cappelletti, Tommaso Fontana,“Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments”, 2020, IEEEAccess
[17] Anwar Jarndal, Saddam Husain, Omar Zaatar, Talal Al Gumaei, Amar Hamadeh, “GPR and ANN based Prediction Models for COVID-19 Death Cases”, 2020, International Conference on Communications, Computing, Cybersecurity, and
Informatics(CCCI)
[18] Huan Zhao, Yichi Li, Shenglan Chu, Suling Zhao, Chenglin Liu, “A COVID-19 Prediction Optimization Algorithm Based on Real-time Neural Network Training—Taking Italy as an Example”, 2021, IEEE Asia-Pacific Conference on Image
Processing, Electronics and Computers(IPEC)
[19] Nanning Zheng, Shaoyi Du, Jianji Wang, He Zhang, Wenting Cui, Zijian Kang, Tao Yang, Bin Lou, Yuting Chi, Hong Long, Mei Ma, Qi Yuan, Shupei Zhang, Dong Zhang, FengYe,JingminXin,“Predicting-COVID-9inChinaUsingHybridAIModel”,
2020, IEEE Transactions on Cybernetics
[20] Safa Bahri, MoetezKdayem, NesrineZoghlami, “Deep Learning for COVID-19 prediction”, 2020 4th International Conference on Advanced Systems and Emergent Technologies(IC_ASET)
[21] Teddy Mantoro, RahmadyaTriasHandayanto, Media Anugerah Ayu, Jelita Asian, “Prediction of COVID-19 Spreading Using Support Vector Regression and Susceptible Infectious Recovered Model”, 2020, 6th International Conference on
Computing Engineering and Design (ICCED)
[22] B. Prabha, Sandeep Kaur, HarikumarPallathadka, “Intelligent predictions of Covid diseasebasedonlungCTimagesusingmachinelearningstrategy”, 2021,MaterialsToday: Proceedings
[23] Wencheng Zou, “The COVID-19 Pandemic Prediction in the US Based on Machine Learning”, 2020, International Conference on Public Health and Data Science (ICPHDS)